multilingual-dictionary-mcp

dictionary_rhymes

Find English words that rhyme with a given word, with options for perfect or near rhymes and adjustable result count.

Instructions

Find words that rhyme with the input word. English only — backed by the offline CMU Pronouncing Dictionary.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "word": "<word>"
    },
    "name": "dictionary_rhymes"
  }
}

Input Schema

Name	Required	Description
`word`	Yes
`limit`	No
`perfect`	No	Perfect rhymes (true) vs near rhymes (false)

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv0.3.4May 3, 2026

changedInput schema / properties / perfect / description

Previous value: -"Perfect rhymes (true) vs near/approximate rhymes (false)"New value: +"Perfect rhymes (true) vs near rhymes (false)"

removedInput schema / properties / word / description
```
Removed value: -"The word to rhyme with"
```

First observedv0.2.0May 3, 2026

TDQS

A3.8/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must disclose behavioral traits. It mentions reliance on the offline CMU Pronouncing Dictionary and English-only support, which is helpful. However, it does not discuss what happens if a word is not found, response format, or any side effects, leaving gaps for an agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: the first states the core function, the second adds context. It is front-loaded, efficient, and contains no extraneous information, making it easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 3 parameters, no output schema, and no annotations, the description provides the essential purpose and language constraint but lacks completeness in terms of parameter behavior, return expectations, and error handling. It is minimally viable but could do more.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33% (only 'perfect' has a description). The tool description adds no parameter information beyond the schema. While the schema includes defaults and constraints, the description does not elaborate on what 'word' expects or how 'limit' affects results, requiring the agent to infer.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Find words that rhyme with the input word.' It uses a specific verb and resource, and distinguishes from siblings like 'dictionary_synonyms' by focusing on rhymes. This is precise and immediately understandable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies 'English only,' which sets a clear language constraint. It does not explicitly contrast with sibling tools like 'dictionary_sounds_like,' but the purpose is specific enough that an agent can infer when to use this tool for rhyming queries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.